By 2028, at least 15% of day-to-day work decisions will be made autonomously by AI agents—up from virtually 0% in 2024, according to Gartner. However, with rapid adoption comes risk: 25% of enterprise breaches will be linked to AI agent abuse.
You might think, we’re not building AI agents, so why worry? The truth is, AI agents are already shaping your business—whether you build them or buy them. Many organizations are integrating ready-to-deploy AI solutions, from chatbots to predictive analytics and supply chain optimizers.
The real challenge isn’t just registering AI agents—it’s managing the data they access, their configurations and deployments across enterprise ecosystems like SAP, SFDC and GCP. To drive innovation while minimizing risk, organizations need a seamless way to connect these elements, ensuring visibility, compliance and control. Without proper governance, AI adoption can quickly turn into a security and compliance minefield, leaving businesses exposed to unforeseen risks.
In this blog, we’ll break down what AI agents are, what’s the challenges with AI agents and why governing them cannot be an afterthought.
What are AI agents?
AI agents are software programs or systems that act autonomously to perform tasks, make decisions or interact with users. These agents rely on artificial intelligence models—such as machine learning or natural language processing—to interpret data, understand instructions and take action to achieve specific goals. Autonomous agents are becoming the backbone of modern AI systems, with their ability to operate independently and adapt to dynamic environments.
AI agents can operate in various domains, including customer service, supply chain management, marketing, human resources and finance.
For example:
- In customer service: Chatbots or virtual assistants respond to customer inquiries, resolving issues without human intervention
- In supply chain management: AI agents optimize inventory levels, schedule deliveries or identify bottlenecks in logistics
- In marketing: AI-powered tools analyze customer behavior, crawl the web for relevant trends and insights, and recommend personalized campaigns to increase engagement
Why governing AI agents cannot be an afterthought
AI agents are transforming the way businesses operate, but they are far from infallible. With the rapid proliferation of these agents, organizations are losing visibility over who owns which agent, what department oversees them, what data they have access to and what actions they can take.
Without proper governance, AI agents can introduce bias, mishandle sensitive data, violate compliance regulations or make decisions misaligned with business objectives. Their ability to operate autonomously—often with limited visibility into how they function—makes them particularly challenging to control.
For example, let’s imagine an AI-powered assistant integrated into an enterprise system that suddenly gains access to the CEO’s confidential files. Without safeguards, it could start summarizing sensitive financial projections or board discussions and inadvertently share them with unauthorized employees or external partners.
As we mentioned during our webinar with Sunil Soares, this challenge is amplified when organizations adopt external AI agents from third-party providers. Many of these solutions function as black boxes, offering little transparency into how decisions are made or whether they align with company policies, compliance frameworks and security protocols. The risk of missteps is enormous, underscoring the urgent need for strong AI governance.
Three challenges on governing AI agents and how Collibra can help
1. Maintaining AI agents reliability
AI agents might interact with sensitive data and critical systems, making them prime targets for cyber threats. Without proper safeguards, they can expose businesses to regulatory penalties, data leaks or even unauthorized decision-making without proper safeguards.
✅ Centralized AI governance frameworks: Collibra equips AI Governance councils to oversee the acquisition, development and deployment of AI agents in alignment with governance policies across all AI systems. By enabling accountability, risk assessment and compliance with ethical and regulatory standards, Collibra ensures that AI agents can operate within well-defined boundaries
✅Keep the human in the loop: Collibra enables AI governance councils to continuously track the performance and outputs of AI agents, identifying and addressing issues like unauthorized data access, bias, errors or misalignment with business goals
✅ Built-in in data reliability: If your AI use cases interact with personal or sensitive data (PI, PII), you’ll see it flagged in the system. If a data category changes and a potential risk occurs, you will be automatically alerted so you can proactively mitigate risks before they impact AI use cases and apply the proper safeguards
2. Struggling with shadow AI and a lack of oversight over agentic AI
AI agents can operate autonomously, making decisions without human intervention. Without a governance framework, unsanctioned or poorly monitored AI—often referred to as shadow AI—can introduce security vulnerabilities, compliance risks and operational inconsistencies.
Furthermore, AI agents often function as opaque systems, making it difficult to understand how they reach conclusions. A lack of explainability can result in biased decisions, poor outcomes and a loss of trust from both stakeholders and regulators.
✅End-to-end traceability: With Collibra, businesses can document AI workflows, enabling stakeholders to understand how AI agents make decisions and control data access. The platform’s explainable AI capabilities ensure that even black-box systems from external vendors can be evaluated for transparency
✅ Collibra data and AI lineage: Organizations gain end-to-end visibility into AI agent decisions, ensuring data origins, risk control and compliance by tracking data flows and model outputs—shedding light on shadow AI and enhancing transparency
3. Manage security and compliance risks associated with AI agents
The EU AI Act classifies AI systems based on risk levels, ranging from minimal to unacceptable risks. AI agents, particularly those used in high-stakes domains like recruitment, finance or healthcare, often fall under strict governance requirements. The Act mandates transparency, accountability and risk mitigation, ensuring AI agents are free from bias and operate ethically. Specifically, if AI agents are classified as High Risk, organizations deploying AI agents in the EU must comply with obligations such as maintaining detailed documentation, enabling human oversight and ensuring explainability. Non-compliance of high-risk systems could result in significant fines of up to 15M € or 3% of GAT ( Global Annual Turnover of the previous fiscal year) making robust AI governance essential.
✅ Built-in data privacy and protection controls: Collibra provides role-based access controls and data protection capabilities to secure sensitive information AI agents process
✅ EU AI Act Compliance Assessment Tool: Collibra helps organizations quickly determine whether their AI systems fall under the EU AI Act’s scope. With built-in assessments and automated guidance, teams can evaluate AI risk levels, classify models based on their risk level and identify key respective compliance obligations. The tool systematizes compliance with the EU AI Act, helping businesses navigate regulations efficiently, make informed AI deployment decisions and reduce legal and operational risks.
Balance innovation and risk management in AI agent deployment
AI agents, whether developed in-house or sourced externally, offer significant value but also introduce challenges related to reliability, traceability and compliance. Ensuring these systems operate securely and transparently is critical, as risks like data security vulnerabilities, vendor lock-in and regulatory complexities can undermine trust. Manual oversight alone is insufficient to manage the scale and velocity of AI-driven interactions.
To address these challenges, organizations must deploy automated monitoring tools that detect and correct anomalies, log decisions for greater transparency and escalate complex cases for human oversight.
Platforms like the Collibra Platform provide a robust framework to develop AI agent usage securely and efficiently without slowing down innovation. By adopting this balanced approach, businesses can confidently unlock the full potential of AI while maintaining control and compliance.
